GIS and Transportation
Keivan Khoshons
GEOG 516
Feb 10, 2004
Outline
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Introduction: What is GIS-T?
Differences between GIS and other Systems
Unique Properties of Geographic Information
GIS Models Used in Transportation
Challenges for GIS-T
Conclusions
What is GIS-T?
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Geographic information systems for transportation (GIS-T) are
interconnected hardware, software, data, people, organizations,
and institutional arrangements for collecting, storing, analyzing,
and communicating particular types of information about the
Earth. “Fletcher, 2000”
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These particular types of information are transportation systems
and geographic regions.
GIS-T can be viewed as the product of the interaction between
improved concepts of both geographic information system (GIS)
and transportation information system (TIS) “Vonderhoe et al., 1993”
What is GIS-T? (cont’d)
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GIS-T as the merger of an enhanced GIS and enhanced
transportation information system (TIS)
(Reference:Vonderhoe et al., 1993)
GIS
TIS
GIS-T
What is GIS-T? (cont’d)
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Some applications:
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infrastructure planning, design and management
traffic safety analysis
transportation impact analysis
public transit planning and operations
intelligent transportation systems (ITS)
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Advanced Traveller Information Systems (ATIS)
Commercial Vehicle Operations (CVO)
Incident Detection Management
Differences between GIS and other Systems
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Multi-functionality
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Geo-visualization capability
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Analytical capability
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makes GIS different from a usual database management
engine;
makes GIS different from an automated mapping
application;
Database management features
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enables GIS to capture spatial and topological
relationship between geo-referenced entities if these
relationships were not pre-defined.
Differences between GIS and other Systems
(cont’d)
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The major difference between GIS and
other database management systems
(DBMS) is mainly in the way information is
referenced rather than the nature of
information handled
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both systems may contain exactly the same
information!
Differences between GIS and other Systems
(cont’d)
An Example
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If we consider total number of accidents occurring in downtown
Vancouver, a DBMS references accidents by some unique index
or combination of indices (e.g., the date of occurrence, the
vehicle make, or the weather conditions). On the other hand,
GIS record each accident as a geographical event with a unique
location defined in a given referencing framework (global,
national or local datum). The spatial referencing of objects
enables users to define topology of data and consequently,
different spatial query operations of objects and set of objects.
Therefore, it is very easy to determine all accidents occurred
within 100 metres of a specific intersection (e.g., Granville and
Robson) on the study area, due to the spatial indexing of all
accidents and roadway link objects in the GIS database.
Differences between GIS and other Systems
(cont’d)
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GIS can produce a spatial representation, or
model, of the data used to describe a portion
of the earth
Unique Properties of Geographic
Information
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Spatial dependency
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The tendency for things closer in geographic space
to be more related
i.e., it is meaningful to record, organize and
analyze data by geographic location.
Spatial heterogeneity
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The tendency of each location in geographic space
to show some degree of uniqueness
i.e., it is valuable to consider local geographic
context rather than just global generalities
Unique Properties of Geographic
Information (cont’d)
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Analytical models and statistical estimation techniques that do
not consider spatial dependencies in geographic data ignore
valuable information and might give misleading results.
With regard to spatial heterogeneity most boundaries are
nothing but misrepresentations of the geographic reality.
Geographic processes such as land-use/
transportation systems and intelligent transportation
systems have properties that non-spatial analysis
techniques do not capture.
GIS Models Used in Transportation
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Field models of the continuous variation of a phenomenon over
space (e.g., land elevation)
Discrete models, depending on which discrete entities (points,
lines or polygons) populate space (e.g., toll barriers, urbanized
areas)
Network models to represent topologically-connected linear
entities (e.g., roads, rail lines) that are fixed in the continuous
reference surface
GIS Models Used in Transportation (cont’d)
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All of these three models are useful in transportation
The network model built around the concept of arc
and node plays the key role in this application
domain because single- and multi-modal
infrastructure networks are vital in enabling and
supporting passenger and freight movement.
In fact, many transportation applications only require
a network model to represent data.
GIS Models Used in Transportation (cont’d)
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However, it is worth noting that advanced
transportation applications, particularly
disaggregate travel demand modelling
approaches and intelligent transportation
systems (ITS), require representation of
complex transportation features that are not
well-supported by the node-arc data model.
GIS Models Used in Transportation (cont’d)
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Goodchild (1998) recognized three meaningful extensions to
overcome these kinds of deficiencies:
 Planner versus non-planner model
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with different representations for topology versus cartography,
by not forcing nodes at cartographic intersections
Turn tables
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for including properties of turning movements
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Properties can be binary (allowed, disallowed), or cardinal
measurements (e.g., expected delay through an intersection)
Links are objects formed of traffic lanes
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A structure that allows for an object-oriented view of the
infrastructure to define topology between lanes
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It may store attributes for individual lanes
GIS Models Used in Transportation (cont’d)
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The need for these and other extensions to the
base network model is not universal and is
dependent to the type of the project.
There are several data modelling, data
manipulation, and data analysis that were not
supported by conventional GIS and currently
are fulfilled by GIS-T software.
Challenges for GIS-T
Legacy data management system
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Transportation agencies keep comprehensive inventories of the
transportation infrastructure, and its condition and usage by the
public.
Each TIS handles a single type of information (e.g., highway
planning network, pavement management system) with its own
data and its own hardware and software platform.
Shortcomings
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Data integration, i.e. to transfer disparate data into a unified data
management system.
Some of the options available
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generic relational data models, new dynamic segmentation data standards,
and object-oriented data models.
Challenges for GIS-T (cont’d)
Data interoperability
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Transportation data are maintained by different agencies and
private data providers
Each data source has its own data model
Accuracy across data sets is varied
Typical errors
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Shortcomings
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Data position, topology, naming and attributing
Algorithms for map matching
Models of error and error spread in transportation data
Data quality standards and data exchange standards
Typical applications
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Commercial Vehicle Operations (CVO)
Advanced Traveller Information Systems (ATIS)
Challenges for GIS-T (cont’d)
Real-time GIS-T
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Real-time traffic data is currently available in many areas
It can be a primary input of world-wide-web applications
However, it does not meet the needs of society when it comes to
geo-referenced data
Shortcomings
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Quicker access data models
More powerful spatial data combination techniques
More powerful dynamic routing algorithms
Challenges for GIS-T (cont’d)
Large data sets
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Transportation problems are complex due to
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Large amounts of geo-referenced data
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Large networks
The complexity combines with difficulty to visualize
information on the single dimension of a network
Shortcomings
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pioneering system designs in order to optimizing
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speed and accuracy of the display of information
the run time of algorithms and analytical tools of network analysis
Challenges for GIS-T (cont’d)
Distributed computing
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Advances in Internet technology have made computing mobile,
distributed and widespread.
Internet GIS applications are currently accessible and common
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Real-time transit route and schedule information
Traffic information
Shortcomings
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More powerful analytical tools to fit
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the limited distributed computing resources, and
limited bandwidth on communication networks
Novel design of system architectures to make efficient use of local
and remote computing resources
Geo-referencing of remote service users and real-time tracking of
their movements
Conclusions
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GIS-T provides the core technology for planning, deploying,
operating, and optimizing transportation systems.
It has opened up new horizons in transportation planning and
engineering.
It has developed an essential tool for the most effective use of
spatial data.
It provides a means of communication for an interactive
understanding between the public and transportation
professionals.
Still, this technology is facing a lot of challenges to adjust itself
with the complexity of transportation data analyses.
Thank You!